Data Science

Heme/Onc consultant: Rapid clinical decision support for hematology and oncology with multi-level analysis. Provides immediate guidance followed by deep adversarial validation, tumor board simulation with multiple specialties, evidence-based research, and risk-benefit analysis. Use for diagnostic dilemmas, treatment planning, complex cases, or when uncertain about clinical decisions in hematology/oncology.

Use when user says "update story tree", "show story tree", "show me a map", "story map", "tree diagram", "show stories", "view stories", "list stories", or asks for story visualization or tree status - autonomously maintains hierarchical story backlog by analyzing git commits, identifying under-capacity nodes, and coordinating story generation to fill gaps. Works with SQLite database using closure table pattern, prioritizes shallower nodes first, and tracks implementation status through commit analysis.

UAF-specific data preparation and validation for time series analysis

Comprehensive AI curriculum development with multi-level content generation, assessment creation, and NotebookLM optimization. Use when creating educational content across beginner through expert skill levels with pedagogical frameworks and learning analytics.

Comprehensive financial analysis suite including investment evaluation, portfolio intelligence, SROI calculation, technology transfer valuation, and cross-border analysis. Use for investment decisions, portfolio management, impact measurement, and financial modeling requiring institutional-grade outputs.

Data analysis, visualization, statistical modeling, and reproducible research workflows.

Provides expert design guidance for creating truthful, clear, beautiful data visualizations. Focuses on **DESIGN DECISIONS ONLY**—chart selection, color strategy, visual encoding, and validation. Assumes data is accurate and prepared. Auto-activates when user mentions: data viz, dashboard, chart type, visualization, infographic

Use when user says "build stories", "generate stories", "create stories", "brainstorm stories", "brainstorm features", "create stories for [node]", or asks for new story ideas. Complete story lifecycle - generates evidence-based stories from git commits and gap analysis, validates quality, vets for conflicts, and retries up to 10 times if duplicates detected. Polishes stories with hold_reason='polish' FIRST before generating new ones. Supports multi-node batching. Does NOT commit - leaves that to caller.

Use this skill for the requests related to load coal mines in USA as GeoDataframe in GeoPandas

Extracts, transforms, and analyzes NBA statistics using the nba_api Python library. Use when working with NBA player stats, team data, game logs, shot charts, league statistics, or any NBA-related data engineering tasks. Supports both stats.nba.com endpoints and static player/team lookups.

Deep dive into memory layout, including strides, C vs Fortran order, and zero-copy view generation via stride tricks. Triggers: strides, C-order, Fortran-order, memory locality, stride_tricks.

Comprehensive guide to phylogenetic tree visualization including matplotlib (Python), ggtree (R), and publication-quality figure generation. Covers rectangular, circular, radial layouts, bootstrap annotations, branch coloring, clade highlighting, and interactive visualizations. Based on best practices from Yulab's Tree Data Book.

WHEN: Coverage analysis, finding untested files, test prioritization, coverage gap identificationWHAT: Line/Branch/Function coverage + untested file list + priority by importance + improvement roadmapWHEN NOT: Test generation → test-generator, Test quality → code-reviewer

Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

This skill should be used when implementing rich, interactive React components in LangGraph applications, including weather dashboards, image galleries, flashcards, charts, forms, and custom visualizations. Use when building new agents with custom UI, retrofitting existing agents with generative UI, or implementing specific component types like galleries or interactive forms.

Fourier transformation for frequency domain analysis

This skill should be used when the user asks to "profile the data", "explore the dataset", "plan the analysis", or as Phase 2 of the /ds workflow after brainstorming. Profiles data and creates analysis task breakdown.

Advanced 3D features including VoxelLayer, PointCloudLayer, weather effects, daylight simulation, glTF model imports, and custom WebGL rendering. Use for volumetric data, LiDAR visualization, and immersive 3D experiences.

Run pytest test suite for the video processing pipeline with coverage analysis. Use when the user wants to run tests, check test coverage, validate code quality, or verify pipeline functionality.

Validation rules, schema checks, duplicate detection, and coverage analysis for golden dataset integrity